Abstract This paper develops an adaptive memory event‐triggered fault detection approach for a class of continuous‐time switched linear systems with persistent dwell‐time (PDT) switching. Unlike conventional dwell‐time or average dwell‐time switching signals, the more common PDT switching signal is considered, which can describe more switching behaviors of dynamic systems. We aim to design an event‐triggered based mode‐dependent fault detection filter, thereby enabling the augmented system that satisfies the desired nonweighted performance. Different from the existing event‐triggered fault detection mechanism, the proposed method has two advantages, that is, one is that it avoids long time without data transmission by designing the minimum real‐time transmission rate and the other one is that it can reduce the false triggering caused by unknown abrupt disturbance and measurement noise. Finally, the effectiveness of the proposed fault detection approach is verified by two examples including a switched RLC circuit.

Abstract The main purpose of this paper is to examine the controllability of linear time‐fractional systems involving the Caputo fractional derivative of order . We first define the concept of controllability and then develop a theoretical framework to demonstrate certain exact and approximate controllability properties of time‐fractional systems. This is achieved using a novel expression for the controllability operator based on the formulation of the mild solution of our problem, fractional calculus theory, and the cosine family. Subsequently, we extend the Hilbert uniqueness method (HUM) approach to determine the optimal control of our problem. Finally, we present numerical simulations for one‐dimensional systems with different types of actuators, either zonal or pointwise, to support the theoretical results discussed in the paper. These simulations achieve a satisfactory error margin, which determines the effectiveness of our method.

Abstract In this paper, we study the output consensus problems for heterogeneous multi‐agent systems (MASs) with a high‐dimensional leader and directed topology, where the followers are subject to unknown uncertainties. First, an observer is designed to estimate leader's unmeasurable states. Then, by using neural network (NN) approximation theory, a neuro‐adaptive controller consists of a compensation part and a cooperative term is proposed. Unlike most existing neuro‐adaptive controllers that utilize some discontinuous functions to eliminate the effects of NN approximation errors, a new class of continuous function is used and thereby the chattering effect is avoided. By using tools from graph theory and stability analysis of dynamical systems, it is proven that asymptotical output consensus can be achieved if the underlying network topology contains a directed spanning tree rooted at the leader and the control parameters are suitably chosen. Finally, a numerical simulation is presented to verify the theoretical result.

Abstract This paper investigates the regional fractional enlarged controllability of parabolic linear systems governed by Riemann–Liouville fractional time derivatives. The goal is to design a control that, while ensuring the fractional derivative of the system's state satisfies predetermined criteria, steers the system's fractional output to a desired state within a designated subregion of the domain. The optimal control is defined using two separate methods: subdifferential theory and the Lagrangian technique. We establish the prerequisites for achieving regional controllability by employing these methods. Finally, a Uzawa‐type algorithm is developed and used in numerical simulations to validate the theoretical results, demonstrating the practicality of the proposed control in real‐world scenarios.

Abstract This paper investigates the adaptive variable‐step predictive (AVSP) control of networked control systems (NCSs) against denial‐of‐service (DoS) attacks. An adaptive variable‐step prediction approach based on cumulative error is formulated to ensure the security of the system against DoS attacks, under which the prediction step varies adaptively in each DoS attacks period. The underlying system is described as a switching system and is categorized into three operation modes based on the presence or absence of DoS attacks and the prediction step size. With piecewise Lyapunov function, sufficient conditions for the design of DoS‐period‐based mode‐dependent controller is established, and the effectiveness is verified by an example.

Abstract In this paper, an autonomous decision‐making method for close‐range rendezvous and approaching to noncooperative target with strong maneuvering is proposed based on the distributed distributional deep determined policy gradient (D4PG), and ground simulation system of rendezvous and approaching is constructed by the improved YOLOv5s and universal robotic arm to verify the effectiveness and feasibility. The contributions of this paper are as follows: (1) an improved nearest neighbor exploration mechanism including random constant value and logarithmic constant value is proposed to stabilize the convergence for the decision‐making under the uncertainty; (2) a discrete wavelet transform (DWT)‐based preprocessing, a fusion of generalized additive model (GAM), and an optimization scheme are proposed for the dark background and false detection of black objects; and (3) a comparison analysis of simulation result between the traditional noise and proposed state‐based exploration is presented for the superiority and some robot‐based ground experiments are done to verify feasibility of close‐range space rendezvous and approaching.

Abstract This paper is concerned with the exact reachability of discrete‐time stochastic system with partial information. The main contribution is to obtain the necessary and sufficient Gramian matrix criterion for the exact reachability of stochastic systems with partial information. The key is to innovatively transform the stochastic system governed by forward stochastic difference equation into an equivalent system governed by backward stochastic difference equation. Simulation examples illustrate the effectiveness of the results.

Abstract Connectivity maintenance is crucial for the real‐world deployment of multi‐agent systems, as it ultimately allows the agents to communicate, coordinate, and perform tasks in a collaborative way. In this paper, a new problem called the dynamic connectivity maintenance problem is considered, which aims to model the scenario where part agents have already broken away from the original communication range but still could be communicated by the other agents. To this end, nearest neighbor‐based methods are proposed in this paper to ensure that the graphs of multi‐agent systems have a spanning tree at all times. Considering that it takes time during the dynamic connectivity maintenance process, this paper also considers the impact of non‐uniform time‐varying time delays on communication and obtains a solution to the gain under the maximum time delay through the Lyapunov method when achieving a consensus. A new approach based on a chain‐type transformation to investigate the consensus problem is proposed. Some sufficient conditions are established. Finally, the developed approaches are validated through a simulation of unmanned surface vessels and a task of autonomous driving truck fleet.

Abstract This paper investigates discrete‐time high‐order fully actuated (DT‐HOFA) robust stabilization control for a type of combined spacecraft simulator (CSS) subject to nonlinear uncertainties. First, a discrete‐time second‐order fully actuated system (FAS) model is developed for the CSS system and generalized to a general DT‐HOFA system (HOFAS) with nonlinear uncertainty, after which the robust control objective is proposed. Then, based on a linear matrix inequality condition, a robust stabilizing controller for the uncertain DT‐HOFAS is designed under certain nonlinear uncertainties, which produces a closed‐loop system with arbitrarily assignable eigenstructure. The assignable nature of the closed‐loop system is further utilized to improve the system performance by solving a multi‐objective optimization problem. Finally, the proposed approach is applied successfully to solve the robust stabilization control task of CSS with nonlinear uncertainties, and simulation and experimental results verify its convenience and effectiveness for practical use.

Abstract The air rudder electromechanical servo system plays a crucial role in ensuring the safe and efficient operation of the aircraft. However, the immeasurable command output and the mismatched channel between input and unknown disturbance bring great challenges to its controller design. To tackle this issue, this study proposes a disturbance compensation‐based feedback linearization servo control strategy. This approach uses a radial basis function neural network‐based nonlinear observer to estimate the immeasurable command output and disturbance. Subsequently, a feedback linearization control algorithm is employed using these estimations to achieve disturbance compensation for the air rudder electromechanical system. Following the Lyapunov stability theorem, it is proved that the stability of the electromechanical servo system under the designed control algorithm can be guaranteed. At last, extensive simulation results are provided to demonstrate the effectiveness of the proposed control approach.